1 citations · 2 across the 8 of their papers we have counts for
8 papers
A Generalist Foundation Model for Total-body PET/CT Enables Diagnostic Reporting and System-wide Metabolic Profiling
Wei Chen, Liang Wu, Shuyi Lu +10
Total-body PET/CT enables system-wide molecular imaging, but heterogeneous anatomical and metabolic signals, approximately 2 m axial coverage, and structured radiology semantics ch…
A Training-Free Framework for Open-Vocabulary Image Segmentation and Recognition with EfficientNet and CLIP
Ying Dai, Wei Yu Chen
This paper presents a novel training-free framework for open-vocabulary image segmentation and object recognition (OVSR), which leverages EfficientNetB0, a convolutional neural net…
BrainStratify: Coarse-to-Fine Disentanglement of Intracranial Neural Dynamics
Hui Zheng, Hai-Teng Wang, Yi-Tao Jing +7
Decoding speech directly from neural activity is a central goal in brain-computer interface (BCI) research. In recent years, exciting advances have been made through the growing us…
LoTLIP: Improving Language-Image Pre-training for Long Text Understanding
Wei Wu, Kecheng Zheng, Shuailei Ma +7
Understanding long text is of great demands in practice but beyond the reach of most language-image pre-training (LIP) models. In this work, we empirically confirm that the key rea…
MePT: Multi-Representation Guided Prompt Tuning for Vision-Language Model
Xinyang Wang, Yi Yang, Minfeng Zhu +3
Recent advancements in pre-trained Vision-Language Models (VLMs) have highlighted the significant potential of prompt tuning for adapting these models to a wide range of downstream…
Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMs
Shi Liu, Kecheng Zheng, Wei Chen
Existing Large Vision-Language Models (LVLMs) primarily align image features of vision encoder with Large Language Models (LLMs) to leverage their superior text generation capabili…
DreamLIP: Language-Image Pre-training with Long Captions
Kecheng Zheng, Yifei Zhang, Wei Wu +5
Language-image pre-training largely relies on how precisely and thoroughly a text describes its paired image. In practice, however, the contents of an image can be so rich that wel…
TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification
Qinying Liu, Wei Wu, Kecheng Zheng +6
The crux of learning vision-language models is to extract semantically aligned information from visual and linguistic data. Existing attempts usually face the problem of coarse ali…